Spectral Clustering: An empirical study of Approximation Algorithms and its Application to the Attrition Problem - B. Cung; T. Jin; Juan Ramirez; A. Thompson; Christos Boutsidis; Deanna Needell (CoRR, 2012)

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. - Jose Gallego-Posada; Juan Ramirez; Akram Erraqabi; Yoshua Bengio; Simon Lacoste-Julien (NeurIPS, 2022)

L0onie: Compressing COINs with L0-constraints. - Juan Ramirez; Jose Gallego-Posada (CoRR, 2022)

Omega: Optimistic EMA Gradients. - Juan Ramirez; Rohan Sukumaran; Quentin Bertrand; Gauthier Gidel (CoRR, 2023)

Balancing Act: Constraining Disparate Impact in Sparse Models. - Meraj Hashemizadeh; Juan Ramirez; Rohan Sukumaran; Golnoosh Farnadi; Simon Lacoste-Julien; Jose Gallego-Posada (ICLR, 2024)

On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization. - Motahareh Sohrabi; Juan Ramirez; Tianyue H. Zhang; Simon Lacoste-Julien; Jose Gallego-Posada (ICML, 2024)

Feasible Learning. - Juan Ramirez; Ignacio Hounie; Juan Elenter; Jose Gallego-Posada; Meraj Hashemizadeh; Alejandro Ribeiro; Simon Lacoste-Julien (AISTATS, 2025)

Cooper: A Library for Constrained Optimization in Deep Learning. - Jose Gallego-Posada; Juan Ramirez; Meraj Hashemizadeh; Simon Lacoste-Julien (CoRR, 2025)

Position: Adopt Constraints Over Penalties in Deep Learning. - Juan Ramirez; Meraj Hashemizadeh; Simon Lacoste-Julien (CoRR, 2025)